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OpenEO Platform - User Story 1

Access of pre-computed data over a large area.

Background - Explore the openEO Platform

Before loading and processing the data, we can have a look at the available collections:

Get the metadata for Sentinel-2 ARD collection:

Authenticate using EGI

Area of Interest selection

Run the next cell, click on the rectangle button and then draw the area over the map like in the following example image

rectangle_selection

Get the bounding box from the previous map.

Sentinel-2

Sentinel-2 L2A ARD (Analysis Ready Data) access

  1. Define collection, time range and bands of interest.
  1. Save operation as final step to the pipeline.
  1. Create a new batch job on the back-end and ask to process it.

We can get a description of the job and check its status.

  1. Once the job status is 'finished', we can download the result and visualize it.

Running the next cell, the Sentinel-2 data will appear on the map as in the following screenshot.

sample_B04

Sentinel-1

Sentinel-1 ARD access

We use the same area as before following the same steps with a different collection

  1. Create a new batch job on the back-end and ask to process it.

Running the next cell, the Sentinel-1 data will appear on the map as in the following screenshot.

sample_VH

Landsat-8

Landsat-8 ARD access

Accessing data from overlapping areas in the original Landsat tiling system.

We can have a look at the original spatial coverage of the ARD Landsat-8 collection, with its four overlapping areas.

We are going to demonstrate that, with the Equi7 grid used in this ARD collection, the data is being reprojected and therefore there are no problems of duplicated data in overlapping areas.

  1. Create a new batch job on the back-end and ask to process it.
  1. Once the job status is 'finished', we can download it.

We can visualize the RGB composite as a simple image using Matplotlib. Notice the seamless integration of the overlapping Landsat tiles.